Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building an autonomous decision engine for digital advertising with an accent on optimization, risk-aware decision systems, and real-time execution. Focus on designing end-to-end ML algorithms, deploying capital into real markets, and ensuring system reliability under uncertainty.

Location: Must be based in or able to work onsite in San Francisco, CA

Salary: $160,000–$250,000 + Equity

Company

An early-stage AI startup applying quantitative finance and high-frequency trading rigor to digital advertising.

What you will do

• Design and implement algorithms for budget allocation and optimization across advertising channels.
• Build predictive models for customer value, performance, and spend efficiency.
• Develop risk-aware decision systems that operate in dynamic, real-time environments.
• Create execution layers for real-time bidding and automated capital deployment.
• Develop simulation and backtesting frameworks for strategy validation.
• Ensure model performance, observability, and reliability in production environments.

Requirements

• Must be able to work onsite in San Francisco, CA.
• Proven experience building and deploying machine learning systems in production.
• Strong foundations in statistics, probability, optimization, and quantitative problem solving.
• Experience owning ML systems end-to-end, from experimentation through deployment and monitoring.
• Strong software engineering skills with a focus on building reliable, scalable systems.
• Experience working with real-world decision systems where model outputs directly drive actions.

Nice to have

• Experience with reinforcement learning or control systems.
• Background in algorithmic trading or financial systems.
• Knowledge of programmatic advertising.
• Experience with forecasting and predictive modeling.